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Research Spotlight: Associate Professor of Business Ming D. Leung on Creating Inclusive Workforces with Atipica Insights

Atipica is proud to partner with Academics, including Paul Merage School of Business Associate Professor Ming D. Leung on these findings.

As someone who studies employment discrimination and bias, I am very excited to partner with Atipica to investigate issues at the heart of creating a more diverse and inclusive workforce. 

While I recognize that there are a myriad of reasons that make this a challenge, one particular area that my fellow researchers and I have been focusing on is to better understand what is occurring during the job application and hiring process. That is, we investigate what happens from the point when a job applicant submits their application all the way through the hiring decision. We believe this is vital because, ultimately, understanding whether, how, or why a job applicant gets hired into a company is a vitally consequential step towards fixing the problem of representation. 

The challenge to developing such an understanding is data. Not that there is a lack of data available – the prevalence of Applicant Tracking Systems alleviates that problem. Instead, it is visibility into what the data is saying that is lacking – the insight. That is where Atipica comes in.

Atipica has been developing the knowledge and ability to produce insight from the data in an organization’s ATS. Insights that cannot readily be gleaned from the ATS itself. Let me give you an example. One question I hear from managers grappling with this issue is that they find it difficult to know the racial and gender breakdown of applicants to their job posting. Self-reported data on this aspect is often missing. Atpica takes the raw data from an organization’s ATS, and utilizing proprietary algorithms, is able to deduce the gender and race of job applicants at a surprisingly accurate rate – providing managers with a real-time snapshot of who it is that is applying to their jobs.

My partnership with Atipica allows me to ask exciting new questions. For example, there has been a trend for people to “job hop” much more today than in the past. But what implications does this job mobility have on getting hired? To answer this, we are examining how the sequence of ones past jobs affects the likelihood that you are called back for an interview. In another project, we are beginning to examine whether and how women and men are treated differently during different phases of the job application process. This is important because prescriptions for how to mitigate potential gender biases in hiring need to take into account why and where it may be occurring. We are not only analyzing whether there are differences in whether women and men may be pre-screened, but also if there are differences in their callback rates, and potential differences in their likelihood of getting the eventual job.

Striving towards a more diverse and inclusive workforce will require a breadth of solutions. I am excited to partner with Atipica to bring one important piece to the puzzle – an understanding as to how the hiring process affects outcomes. I believe that novel understanding and solutions can only be realized through creating insights from data. This is the link that Atipica provides.

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